Power grid defect detection method and system

A defect detection and power grid inspection technology, applied in the field of computer vision, can solve problems such as difficult to meet industrial use requirements, poor detection effect, model redundancy calculation, etc., achieve simple and effective ideas, improve detection performance, and improve accuracy Effect
CN113012107AActive Publication Date: 2021-06-22JIANGSU FRONTIER ELECTRIC TECH

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
JIANGSU FRONTIER ELECTRIC TECH
Publication Date
2021-06-22

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Abstract

The embodiment of the invention provides a power grid defect detection method and system, and the method comprises the steps: obtaining a feature map corresponding to a to-be-detected power grid inspection image, the feature map comprises a plurality of grid points, and each grid point corresponds to one region of the image; grid points in the feature map are divided into a first class and a second class, the first class represents a defect area, and the second class represents a background area; merging the grid points of the first type to obtain a connected domain; and inputting the connected domain into a pre-trained target detection network to obtain a defect detection result output by the network. According to the embodiment of the invention, the proportion of the defect target in the whole picture is very low for the power grid inspection picture which is data with a complex background, and the accuracy of the model can be obviously improved by extracting the target and then performing classification regression on the target through a coarse-to-fine rapid power grid defect detection method.
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Description

technical field

[0001] The invention relates to the field of computer vision, and more specifically, to a method and system for detecting defects in a power grid. Background technique

[0002] Object detection is one of the basic tasks in the field of computer vision, which has been researched for nearly two decades in academia. In recent years, with the rapid development of deep learning technology, the target detection algorithm has also shifted from the traditional algorithm based on manual features to the detection technology based on deep neural network. The performance of the target detection algorithm based on deep learning is significantly better than that of traditional methods. It has been widely used in many fields such as robot navigation, intelligent video surveillance, industrial inspection, aerospace, etc. It has important practical significance to reduce the consumption of human capital through computer vision. significance.

[0003] The current mainstream ...

Claims

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